Determination of transgenic loci by expression FISH

Single-Cell Multiomics

Single-cell RNA sequencing methods have led to improved understanding of the heterogeneity and transcriptomic states present in complex biological systems. Recently, the development of novel single-cell technologies for assaying additional modalities, specifically genomic, epigenomic, proteomic, and spatial data, allows for unprecedented insight into cellular biology. While certain technologies collect multiple measurements from the same cells simultaneously, even when modalities are separately assayed in different cells, we can apply novel computational methods to integrate these data. The application of computational integration methods to multimodal paired and unpaired data results in rich information about the identities of the cells present and the interactions between different levels of biology, such as between genetic variation and transcription. In this review, we both discuss the single-cell technologies for measuring these modalities and describe and characterize a variety of computational integration methods for combining the resulting data to leverage multimodal information toward greater biological insight.

Technique integration of single-cell RNA sequencing with spatially resolved transcriptomics in the tumor microenvironment

Background

The tumor microenvironment contributes to tumor initiation, growth, invasion, and metastasis. The tumor microenvironment is heterogeneous in cellular and acellular components, particularly structural features and their gene expression at the inter-and intra-tumor levels.

Main text

Single-cell RNA sequencing profiles single-cell transcriptomes to reveal cell proportions and trajectories while spatial information is lacking. Spatially resolved transcriptomics redeems this lack with limited coverage or depth of transcripts. Hence, the integration of single-cell RNA sequencing and spatial data makes the best use of their strengths, having insights into exploring diverse tissue architectures and interactions in a complicated network. We review applications of integrating the two methods, especially in cellular components in the tumor microenvironment, showing each role in cancer initiation and progression, which provides clinical relevance in prognosis, optimal treatment, and potential therapeutic targets.

Conclusion

The integration of two approaches may break the bottlenecks in the spatial resolution of neighboring cell subpopulations in cancer, and help to describe the signaling circuitry about the intercommunication and its exact mechanisms in producing different types and malignant stages of tumors.

Spatial omics: Navigating to the golden era of cancer research

The idea that tumour microenvironment (TME) is organised in a spatial manner will not surprise many cancer biologists; however, systematically capturing spatial architecture of TME is still not possible until recent decade. The past five years have witnessed a boom in the research of high-throughput spatial techniques and algorithms to delineate TME at an unprecedented level. Here, we review the technological progress of spatial omics and how advanced computation methods boost multi-modal spatial data analysis. Then, we discussed the potential clinical translations of spatial omics research in precision oncology, and proposed a transfer of spatial ecological principles to cancer biology in spatial data interpretation. So far, spatial omics is placing us in the golden age of spatial cancer research. Further development and application of spatial omics may lead to a comprehensive decoding of the TME ecosystem and bring the current spatiotemporal molecular medical research into an entirely new paradigm.

Statistical and machine learning methods for spatially resolved transcriptomics with histology

Recent developments in spatially resolved transcriptomics (SRT) technologies have enabled scientists to get an integrated understanding of cells in their morphological context. Applications of these technologies in diverse tissues and diseases have transformed our views of transcriptional complexity. Most published studies utilized tools developed for single-cell RNA sequencing (scRNA-seq) for data analysis. However, SRT data exhibit different properties from scRNA-seq. To take full advantage of the added dimension on spatial location information in such data, new methods that are tailored for SRT are needed. Additionally, SRT data often have companion high-resolution histology information available. Incorporating histological features in gene expression analysis is an underexplored area. In this review, we will focus on the statistical and machine learning aspects for SRT data analysis and discuss how spatial location and histology information can be integrated with gene expression to advance our understanding of the transcriptional complexity. We also point out open problems and future research directions in this field.

Strategies and technologies for exploring long noncoding RNAs in heart failure

Long non-coding RNA (lncRNA) was once considered to be the "noise" of genome transcription without biological function. However, increasing evidence shows that lncRNA is dynamically expressed in developmental stage or disease status, playing a regulatory role in the process of gene expression and translation. In recent years, lncRNA is considered to be a core node of functional regulatory networks that controls cardiac and also involves in multiple process of heart failure such as myocardial hypertrophy, fibrosis, angiogenesis, etc., which would be a therapeutic target for diseases. In fact, it is the development of technology that has improved our understanding of lncRNAs and broadened our perspective on heart failure. From transcriptional "noise" to star molecule, progress of lncRNAs can't be achieved without the combination of multidisciplinary technologies, especially the emergence of high-throughput approach. Thus, here, we review the strategies and technologies available for the exploration lncRNAs and try to yield insights into the prospect of lncRNAs in clinical diagnosis and treatment in heart failure.

Uncovering an Organ's Molecular Architecture at Single-Cell Resolution by Spatially Resolved Transcriptomics

Revealing fine-scale cellular heterogeneity among spatial context and the functional and structural foundations of tissue architecture is fundamental within biological research and pharmacology. Unlike traditional approaches involving single molecules or bulk omics, cutting-edge, spatially resolved transcriptomics techniques offer near-single-cell or even subcellular resolution within tissues. Massive information across higher dimensions along with position-coordinating labels can better map the whole 3D transcriptional landscape of tissues. In this review, we focus on developments and strategies in spatially resolved transcriptomics, compare the cell and gene throughput and spatial resolution in detail for existing methods, and highlight the enormous potential in biomedical research.

Technological Developments in lncRNA Biology

It is estimated that more than 90% of the mammalian genome is transcribed as non-coding RNAs. Recent evidences have established that these non-coding transcripts are not junk or just transcriptional noise, but they do serve important biological purpose. One of the rapidly expanding fields of this class of transcripts is the regulatory lncRNAs, which had been a major challenge in terms of their molecular functions and mechanisms of action. The emergence of high-throughput technologies and the development in various conventional approaches have led to the expansion of the lncRNA world. The combination of multidisciplinary approaches has proven to be essential to unravel the complexity of their regulatory networks and helped establish the importance of their existence. Here, we review the current methodologies available for discovering and investigating functions of long non-coding RNAs (lncRNAs) and focus on the powerful technological advancement available to specifically address their functional importance.

In Situ Transcription Profiling of Single Cells Reveals Spatial Organization of Cells in the Mouse Hippocampus

Identifying the spatial organization of tissues at cellular resolution from single-cell gene expression profiles is essential to understanding biological systems. Using an in situ 3D multiplexed imaging method, seqFISH, we identify unique transcriptional states by quantifying and clustering up to 249 genes in 16,958 cells to examine whether the hippocampus is organized into transcriptionally distinct subregions. We identified distinct layers in the dentate gyrus corresponding to the granule cell layer and the subgranular zone and, contrary to previous reports, discovered that distinct subregions within the CA1 and CA3 are composed of unique combinations of cells in different transcriptional states. In addition, we found that the dorsal CA1 is relatively homogeneous at the single cell level, while ventral CA1 is highly heterogeneous. These structures and patterns are observed using different mice and different sets of genes. Together, these results demonstrate the power of seqFISH in transcriptional profiling of complex tissues.

Single-molecule RNA detection at depth by hybridization chain reaction and tissue hydrogel embedding and clearing

Accurate and robust detection of mRNA molecules in thick tissue samples can reveal gene expression patterns in single cells within their native environment. Preserving spatial relationships while accessing the transcriptome of selected cells is a crucial feature for advancing many biological areas – from developmental biology to neuroscience. However, because of the high autofluorescence background of many tissue samples, it is difficult to detect single-molecule fluorescence in situ hybridization (smFISH) signals robustly in opaque thick samples. Here, we draw on principles from the emerging discipline of dynamic nucleic acid nanotechnology to develop a robust method for multi-color, multi-RNA imaging in deep tissues using single-molecule hybridization chain reaction (smHCR). Using this approach, single transcripts can be imaged using epifluorescence, confocal or selective plane illumination microscopy (SPIM) depending on the imaging depth required. We show that smHCR has high sensitivity in detecting mRNAs in cell culture and whole-mount zebrafish embryos, and that combined with SPIM and PACT (passive CLARITY technique) tissue hydrogel embedding and clearing, smHCR can detect single mRNAs deep within thick (0.5 mm) brain slices. By simultaneously achieving ∼20-fold signal amplification and diffraction-limited spatial resolution, smHCR offers a robust and versatile approach for detecting single mRNAs in situ, including in thick tissues where high background undermines the performance of unamplified smFISH.

Summary: Single-molecule hybridization chain reaction, combined with tissue clearing, allows the near-quantitative and spatially localized detection of mRNAs in thick tissue samples.

RNA fluorescence in situ hybridization in cultured mammalian cells

It is now clear that long noncoding RNAs (lncRNAs) regulate a number of aspects of nuclear organization and gene expression. An important tool for the study of the distribution and function of lncRNAs is RNA fluorescence in situ hybridization (RNA-FISH). The protocols presented in this chapter describe this method in detail and also mention a number of critical points that must be considered when performing this technique.

Histone h1 depletion impairs embryonic stem cell differentiation

Pluripotent embryonic stem cells (ESCs) are known to possess a relatively open chromatin structure; yet, despite efforts to characterize the chromatin signatures of ESCs, the role of chromatin compaction in stem cell fate and function remains elusive. Linker histone H1 is important for higher-order chromatin folding and is essential for mammalian embryogenesis. To investigate the role of H1 and chromatin compaction in stem cell pluripotency and differentiation, we examine the differentiation of embryonic stem cells that are depleted of multiple H1 subtypes. H1c/H1d/H1e triple null ESCs are more resistant to spontaneous differentiation in adherent monolayer culture upon removal of leukemia inhibitory factor. Similarly, the majority of the triple-H1 null embryoid bodies (EBs) lack morphological structures representing the three germ layers and retain gene expression signatures characteristic of undifferentiated ESCs. Furthermore, upon neural differentiation of EBs, triple-H1 null cell cultures are deficient in neurite outgrowth and lack efficient activation of neural markers. Finally, we discover that triple-H1 null embryos and EBs fail to fully repress the expression of the pluripotency genes in comparison with wild-type controls and that H1 depletion impairs DNA methylation and changes of histone marks at promoter regions necessary for efficiently silencing pluripotency gene Oct4 during stem cell differentiation and embryogenesis. In summary, we demonstrate that H1 plays a critical role in pluripotent stem cell differentiation, and our results suggest that H1 and chromatin compaction may mediate pluripotent stem cell differentiation through epigenetic repression of the pluripotency genes.

Profiling of linker histone variants in ovarian cancer

H1 linker histones play a key role in facilitating higher order chromatin folding. Emerging evidence suggests that H1 and its multiple variants are important epigenetic factors in modulating chromatin function and gene expression. Ovarian cancer is a devastating disease, ranking the fifth leading cause of all women cancer death due to its poor prognosis and difficulty in early diagnosis. Although epigenetic alterations in ovarian cancers are being appreciated in general, the role of H1 has not been explored. Here, using quantitative RT-PCR assays, we systematically examined the expression of 7 H1 genes in 33 human epithelial ovarian tumors. Whereas the expression of H1.3 was markedly increased, the expression of H10, H1.1, H1.4 and H1x were significantly reduced in malignant adenocarcinomas compared with benign adenomas. Strikingly, ovarian adenocarcinomas and adenomas exhibited characteristic expression patterns, and expression profiling of 7 H1 genes in tumor samples discriminated adenocarcinomas vs. adenomas with high accuracy. These findings indicate that the expression of H1 variants is exquisitely regulated and may serve as potential epigenetic biomarkers for ovarian cancer.

FISH glossary: an overview of the fluorescence in situ hybridization technique

The introduction of FISH (fluorescence in situ hybridization) marked the beginning of a new era for the study of chromosome structure and function. As a combined molecular and cytological approach, the major advantage of this visually appealing technique resides in its unique ability to provide an intermediate degree of resolution between DNA analysis and chromosomal investigations while retaining information at the single-cell level. Used to support large-scale mapping and sequencing efforts related to the human genome project, FISH accuracy and versatility were subsequently capitalized on in biological and medical research, providing a wealth of diverse applications and FISH-based diagnostic assays. The diversification of the original FISH protocol into the impressive number of procedures available these days has been promoted throughout the years by a number of interconnected factors: the improvement in sensitivity, specificity and resolution, together with the advances in the fields of fluorescence microscopy and digital imaging, and the growing availability of genomic and bioinformatic resources. By assembling in a glossary format many of the "acronymed" FISH applications published so far, this review intends to celebrate the ability of FISH to re-invent itself and thus remain at the forefront of biomedical research.

Cyclin D1 determines mitochondrial function in vivo

The cyclin D1 gene encodes a regulatory subunit of the holoenzyme that phosphorylates and inactivates the pRb tumor suppressor to promote nuclear DNA synthesis. cyclin D1 is overexpressed in human breast cancers and is sufficient for the development of murine mammary tumors. Herein, cyclin D1 is shown to perform a novel function, inhibiting mitochondrial function and size. Mitochondrial activity was enhanced by genetic deletion or antisense or small interfering RNA to cyclin D1. Global gene expression profiling and functional analysis of mammary epithelial cell-targeted cyclin D1 antisense transgenics demonstrated that cyclin D1 inhibits mitochondrial activity and aerobic glycolysis in vivo. Reciprocal regulation of these genes was observed in cyclin D1-induced mammary tumors. Cyclin D1 thus integrates nuclear DNA synthesis and mitochondrial function.

H1 linker histones are essential for mouse development and affect nucleosome spacing in vivo

Most eukaryotic cells contain nearly equimolar amounts of nucleosomes and H1 linker histones. Despite their abundance and the potential functional specialization of H1 subtypes in multicellular organisms, gene inactivation studies have failed to reveal essential functions for linker histones in vivo. Moreover, in vitro studies suggest that H1 subtypes may not be absolutely required for assembly of chromosomes or nuclei. By sequentially inactivating the genes for three mouse H1 subtypes (H1c, H1d, and H1e), we showed that linker histones are essential for mammalian development. Embryos lacking the three H1 subtypes die by mid-gestation with a broad range of defects. Triple-H1-null embryos have about 50% of the normal ratio of H1 to nucleosomes. Mice null for five of these six H1 alleles are viable but are underrepresented in litters and are much smaller than their littermates. Marked reductions in H1 content were found in certain tissues of these mice and in another compound H1 mutant. These results demonstrate that the total amount of H1 is crucial for proper embryonic development. Extensive reduction of H1 in certain tissues did not lead to changes in nuclear size, but it did result in global shortening of the spacing between nucleosomes.

Mammalian linker-histone subtypes differentially affect gene expression in vivo

Posttranslational modifications and remodeling of nucleosomes are critical factors in the regulation of transcription. Higher-order folding of chromatin also is likely to contribute to the control of gene expression, but the absence of a detailed description of the structure of the chromatin fiber has impaired progress in this area. Mammalian somatic cells contain a set of H1 linker-histone subtypes, H1 (0) and H1a to H1e, that bind to nucleosome core particles and to the linker DNA between nucleosomes. To determine whether the H1 histone subtypes play differential roles in the regulation of gene expression, we combined mice lacking specific H1 histone subtypes with mice carrying transgenes subject to position effects. Because position effects result from the unique chromatin structure created by the juxtaposition of regulatory elements in the transgene and at the site of integration, transgenes can serve as exquisitely sensitive indicators of chromatin structure. We report that some, but not all, linker histones can attenuate or accentuate position effects. The results suggest that the linker-histone subtypes play differential roles in the control of gene expression and that the sequential arrangement of the linker histones on the chromatin fiber might regulate higher-order chromatin structure and fine-tune expression levels.